HI-FIVE (Health Informatics For Innovation, Value & Enrichment) Training is a 12-hour online course designed by Columbia University in 2016, with sponsorship from the Office of the National Coordinator for Health Information Technology (ONC). The training is role-based and uses case scenarios. Also, it has additional, optional modules on other topics of interest or relevance. Although we suggest to complete the course within a month's timeframe, the course is self-paced and so you can start and finish the course at anytime during a month's time period. No additional hardware or software are required for this course.
Our nation’s healthcare system is changing at a rapid pace. Transformative health care delivery programs depend heavily on health information technology to improve and coordinate care, maintain patient registries, support patient engagement, develop and sustain data infrastructure necessary for multi-payer value-based payment, and enable analytical capacities to inform decision making and streamline reporting. The accelerated pace of change from new and expanding technology will continue to be a challenge for preparing a skilled workforce so taking this training will help you to stay current in the dynamic landscape of health care.
This course is one of three related courses in the HI-FIVE training program, which has topics on population health, care coordination and interoperability, value-based care, healthcare data analytics, and patient-centered care. Each of the three courses is designed from a different perspective based on various healthcare roles. This first course is from a clinical perspective, geared towards physicians, nurse practitioners, physician assistants, nurses, clinical executives and managers, medical assistants, and other clinical support roles. However, we encourage anyone working in healthcare, health IT, public health, and population health to participate in any of the three trainings.

教学方

Rita Kukafka

脚本

Welcome to Value-Based Care, value based quality and safety, this is lecture e, process improvement. This lecture focuses on the foundations of quality and process improvement and Value-Based Care. The objectives for this lecture, Process Improvement, are to identify the performance and financial drivers of quality improvement. Understand the process steps of quality improvement, and describe the role of health IT in quality improvement. The push for value based care with its emphasis on incentivizing improvement and the quality of care has led us to an examination of methods for achieving quality goals. There are many process improvement methods and tools available, but all of them have some basic similarities. Three seemingly simple questions that the health services researcher Robert Brook posed almost 40 years ago, capture the essence of process improvement methods. The questions are, where am I going? How will I get there? And how will I know I've arrived? In this lecture, we will explore each of these questions from the stand point of process improvement strategies and the help IT tools that support those strategies. The PDSA or Plan, do study, act model for quality improvement promoted by the Institute for Health Care Improvement, is a well know example of the application of these questions to quality improvement. Actually, in the planning stage all three questions are addressed. The initial plans involves setting goals. Deciding on what you will do to achieve the goals. How will I get there? Deciding on what you will study to determine if they are met. How will I know I've arrived and what actions you will take if they are or are not met? The cycle implies that if the initial goals are not met, the planning stage will begin again, reassessing the answer to the three questions. In addition to the PDSA model for process improvement, the Lean and Six Sigma model have similar steps It is critical that quality improvement efforts in health care organizations are organized around the simple premise of asking, what are we trying to improve? That is, where am I going? And then, selecting the right tool from process improvement tool box. How will I get there? For example, Lean methods focus on reducing waste, measuring how work is done, its flow and improving on the flow itself. On the other hand Six Sigma focuses on reducing variation in the processes that create output and resolving existing problems that impede the process. Both Lean and Six Sigma can be used simultaneously, with each approach reflecting a specific component of process improvement. Both of these methods also include measurement to determine how you will know you've arrived. So let's look at what we need to do for applying these methods in the context of value-based care. Governmental agencies are beginning to enforce high quality outcomes across the care continuum. In the new of era of value based care and pay for performance, patient outcomes are clearly linked to financial incentives for health care organizations. Because of this connection, quality improvement is becoming an important facet of how healthcare organizations manage care processes. Quality improvement is driven by the utilization of process improvement tools, including specific methods like Lean and Six Sigma, as well as the use of information technology. Each quality project required step by step definitions of the process improvement goals. Organizations seeking to optimize value based care and take advantage of the incentives can focus on improvement areas that will lead to financial incentives. So with value based care as the context let us look at how we can answer Brooks three questions. There are national quality measures that will be linked to reimbursement. Review of these measures should be considered as a first step. A preliminary assessment of the organization's current performance on these measures serves two functions. First, to determine the current status the measurement, approaches and tools need to be identified, developed and deployed. This is will form the baseline data to compare against future data, when the improvement interventions have been tried. Second, the data will help determine which areas need to be targeted for improvement and what areas should be prioritized. In addition to the National Quality Measures, there may be organizations specific goals. While some of these will come from a similar pre-assessment others may have already been identified. These two need to be prioritized, especially in the context of the need to address the targets for the national quality measures. As part of the prioritizing, assessment of the cost of developing quality improvement interventions versus the potential fiscal costs in not working on each area need to be considered. In the days before most health care providers were using EHRs, getting information on the process and outcomes of care required very labor intensive chart review. With much of the data now in electronic form, and especially with the use of data warehouses that are optimized for queries across multiple patients, data to identify current processes and outcomes can be more easily obtained. However, to get usable data will require good analytic staff as well as strategies to mind clinical notes that may be in text format. Rather than formats that are more easily able to be queried there are some processes and outcomes that may not be included in the EHR. Actual observation of process may be to be done, as well as surveys of providers and other staff. Similarly, although many patient outcomes will be recorded in the medical record, some will not. Patient satisfaction surveys and methods to capture patient reported outcomes such as quality of life, depressed affect, or ability to perform activities of daily living, may be needed. Finally, claims data can be used in conjunction with the process and outcome data to determine the value of care. That is outcomes per data spent. These data can help identify targets for cost reduction, as well as quality improvement. We will talk about some of the assessment strategies that can be used for both pre-assessment, and to assess whether the target goals have been met. When we talk about measurement later in this lecture. But the next step after determining goals and quality and cost targets, will examine ways to answer the question, how will I get there? There are a variety of health information technology tools that can aid in process improvement. The use of clinical decision support, or CDS tools, have been a core requirement of the stage one and two meaningful use requirements. CDS is still a key element in the use of health IT to improve the quality of care. While many people are familiar with alerts and reminders, there are other types of CDS, including order sets and even the configuration of the EHR itself. The CDS can be focused to target the key quality measures. For instance, order sets for diabetic patients can be included in the EHR that include ordering hemoglobin A1C at appropriate intervals. An example of configuring the EHR may be to have an easily accessible place to document smoking status. Setting up these tools is the first step. Monitoring their use and the impact on patient care must follow. Registries tied to reporting requirements cannot only speed up reporting. They can also be used to improve quality. Disease specific registries can include information on the full population of patients with a given condition and can be reviewed to determine if the required procedures have been done. Dashboards that show each provider how they are performing on the quality metrics provide useful feedback that can improve performance. Anonymize comparative metrics can also be included so that Providers can compare themselves to their colleagues. If providers are to utilize these tools, the tools themselves need to be designed with usability in mind, and the end users will need training on how to use them. In addition, they should be set up in a way that also allows users to provide feedback on how well the tools are working and whether they need modification. Once the plan tools are implemented, there use needs to be evaluated. The assessment methods that were used pre-implementation can be deployed again and improvement from baseline measures can be assessed. In addition, the data in the dashboards that were initially geared for individual feedback to clinicians, can be aggregated to assess overall improvement and can also be analyzed by individual. Using these data you can assess weather you have met your target, quality, and cost goals, if you have met those goals the cycle begins again with new targets. And if you have not met your goals, there is a need to examine all parts of the process. The goals themselves need to be examined, were they unrealistic? Or were they realistic, but the timeframe for achieving them was not realistic? If that is the case, more reasonable goals should be set. If upon review the goals were appropriate, you need to look at the processes used to achieve them. You may find that the methods you chose were not working perhaps the type of intervention was not appropriate for the goals. It is an example, if your goal was to increase the percentage of hemoglobin A1C tests ordered for diabetic patients, there are several potential strategies you might choose. If you chose to have educational sessions on the importance of ordering the test, and you did not find a change, you might consider a different strategy. For instance, including the A1C test in an order set for each diabetic patient, making it easy for the clinician to remember to order it at the point of care. On the other hand, the methods may have been appropriate, but perhaps they were not being used. Going back to the example with order sets, if they were not used, the clinicians might have needed training on both how and why to use the order sets. Or perhaps you included alerts and reminders to improve safety, and found that they were being ignored, which frequently happens. By examining how the alerts were set up, how frequently they fired, and under what circumstances they were attended to or ignored, you might be able to come up with a different strategy for use. The main thing is to examine all of the processes and determine what needs to change. Finally, if the goals and methods seem to be appropriate but the metrics did not indicate improvement. The metrics themselves and how they were calculated need to be reviewed just to assure tha the results are accurate. In addition to retrospective review to identify quality problems and work to improve them proactive ongoing monitoring should be done. This may involved periodic review of the dashboards that we discussed but there are other strategies. The Morbidity & Mortality Conferences are a time-honored way to examine the causes of adverse events or quality problems. Another approach is the use of trigger tools, which can identify data that may signal a problem that requires further investigation. There are a variety of tools that can be used for this purpose. A focal point of the Institute for Health Care Improvement, trigger tools provide an efficient way by which an outcome and its associated processes can be examined. Trigger tools are used to identify the indicators of events that lead to, or cause, harm to a patient. They can be used to quickly screen medical records to select those that need further review to determine if there really is a problem with care. The content triggers and the charts are specific to the area of improvement being examined. Adverse drug events are often not reported and can be difficult to detect but proxies have been used to identify potential adverse events. For instance, if one were trying to find adverse drug events, one could look for the administration of an antidote to a drug overdose. Finding such data would trigger a more complete review of the whole record. The IHI has developed a Global Trigger Tool that allows an organization to track its overall adverse event rates, as well as specific Trigger Tools for specific areas of adverse events. A study by David Klassen and colleagues compared the use of the global trigger tool to voluntary reporting and using AHRQs patient safety indicators. Records identified by the trigger tool were reviewed to determine if there was an adverse event. The study found that the global trigger tool found ten times as many adverse events as the other, more traditional methods of finding adverse events. There are also specific trigger tools for particular areas or specialties, such as tools to identify potential adverse surgical events. Trigger tools are clearly a key strategy available for the quality improvement process. They provide specific data that allows an organization to identify adverse event rates in an efficient way. Examples of data gathered through the use of trigger tools include adverse events per 1,000 patient days. Adverse events per 100 admissions, and percent of admissions with an adverse event. Improvement efforts to reduce harm require tracking of measures related to the area of focus. Although trigger tools systematize the review process, if the review is entirely manual the process is still labor intensive. Since Records identified by trigger tools still require additional manual review. The process can be even more efficient if algorithms can be developed that use the criteria in the tool to automatically screen to EHR. The EHR can be mined on a regular basis for problematic events, such as medication errors or missed diagnoses. There have been some efforts to develop automated trigger tools. For instance, and colleagues developed algorithms to identify potential diagnostic errors. They mind the EHR for instances where a patient was hospitalized within a few weeks after a primary care visit and found likely diagnostic errors. In summary, in addition to clinical decision support and other health IT tools designed to address specific quality problems. The use of trigger tools and other ongoing monitoring methods can detect problems, setting the stage for a new set of quality improvement goals. This concludes lecture e of value-based quality and safety. We have discussed the importance of working to improve quality and value based care. And have identified a set of questions that are common to many common methods of process improvement including Lean, Six Sigma, and others. The questions, where am I going, how will I get there, and how will I know I've arrived can assist in articulating goals, methods, and metrics for process improvement.